Convex Optimization
An MMSE approach to the secrecy capacity of the MIMO Gaussian wiretap channel
EURASIP Journal on Wireless Communications and Networking - Special issue on wireless physical layer security
Capacity of cognitive interference channels with and without secrecy
IEEE Transactions on Information Theory
The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel
IEEE Transactions on Information Theory
Multiple-Access Channels With Confidential Messages
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Optimized transmission for fading multiple-access and broadcast channels with multiple antennas
IEEE Journal on Selected Areas in Communications
Robust beamforming design: From cognitive radio MISO channels to secrecy MISO channels
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
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This paper studies the achievable rates of the multi-antenna or multiple-inputmultiple-output (MIMO) secrecy channel with multiple single-/multi-antenna eavesdroppers. By assuming Gaussian input, the maximum achievable secrecy rate is obtained with the optimal transmit covariance matrix that maximizes the minimum difference between the channel mutual information of the secrecy user and those of the eavesdroppers. The maximum secrecy rate computation can thus be formulated as a non-convex max-min problem, which cannot be solved efficiently by existing methods. To handle this difficulty, this paper explores a new relationship between the secrecy channel and the recently developed cognitive radio (CR) channel, in which the secondary user transmits over the same spectrum simultaneously with multiple primary users, subject to the received interference power constraints at the primary users, or the so-called "interference temperature (IT)" constraints. By constructing an auxiliary multi-antenna CR channel that has the same channel responses as the secrecy channel, this paper shows that the optimal transmit covariance to achieve the maximum secrecy rate is the same as that to achieve the CR spectrum sharing capacity with properly selected IT constraints. Thereby, finding the optimal complex transmit covariance matrix for the secrecy channel becomes equivalent to searching over a set of real IT constraints in the auxiliary CR channel. Based on this relationship, efficient algorithms are proposed to solve the non-convex secrecy rate maximization problem by transforming it into a sequence of convex CR spectrum sharing capacity computation problems, under various setups of the secrecy channel.